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The need for businesses to process and analyze data has grown in intensity along with the volumes of data they are amassing. Our benchmark research consistently shows that preparing data is the most widespread impediment to analytic and operational efficiency. In our recent research on data and analytics in the cloud, more than half (55%) of organizations said that preparing data for analysis is a major impediment, followed by other preparatory tasks: reviewing data for quality and consistency (48%) and waiting for data and information (28%). Organizations that want to apply analytics to make more effective decisions and take prompt actions need to find ways to shorten the work that comes before it. Conventional analytics and business intelligence tools are not designed for data preparation, but new software tools can enable business users independently or in concert with IT to perform the tasks needed.
Datawatch offers one such tool, which I have described as doing advanced information optimization. The company has helped organizations get more out of their information assets for years. One could argue that Datawatch has been doing data preparation longer than anyone else in the market; its Monarch product dates back to the 1990s and specializes in extracting and manipulating data from a range of documents and systems. The latest release, version 13, takes significant steps forward with a new user environment and functionality designed for analysts and users in operational positions who need a more intuitive approach to data preparation. Its drag-and-drop approach helps make data preparation doable for most business users.
Datawatch has continued to expand its data access support for various systems including salesforce.com and Hadoop for big data, providing support for both cloud-based and on-premises systems. It has significant support already for the PDF, JSON, and XML standards, as well as text, invoices, documents and log files. It also enables getting data from and putting data back into Microsoft Excel spreadsheets. Datawatch takes an “inspect and recommend” approach to data preparation, which can be especially useful with unstructured data in documents and files. Monarch can identify the data’s format and structure, present what can be extracted and enable setup of a template to use with similar data. A capability the company calls reliable redaction helps in sharing information; after data is extracted it applies masking for privacy purposes to ensure that no regulations and compliance policies are violated. Monarch also supports dataset preparation with many analytic tools like Tableau in which users struggle to access, blend, enrich and use data. Datawatch also has a visual analytics tool it acquired that complements its data preparation.
As organizations examine Datawatch’s tool, they should be aware that it is for more than one-off data preparation, providing a repeatable approach that can save time not only for individuals but for entire teams. Datawatch enables many individuals to share data and collaborate on work. This helps analysts and operations professionals work together, as well as involving IT in complex data-related processes.
Datawatch continues to grow its customer base in data preparation. A prominent example is Marbridge Foundation, which we recognized with our 2015 Leadership Award in Information Optimization for its work to make content and data from its systems comply with the Affordable Care Act – a project driven by its CFO. Marbridge took advantage of the flexibility in Datawatch’s software to extract and process data from Adobe Acrobat files in PDF format along with other applications to gain confidence that it is in compliance with this critical legislation. Data preparation provides the most value in lines of business such as finance, human resources, operations, marketing, sales, operations, customer and supply chain. Having a tool for data preparation that connects to business processes can produce significant impacts.
Data preparation software serves a growing market of business users who need to handle data but are not adept enough to do it with general analytics and business intelligence tools or to use data integration tools intended for IT professionals. Software providers that still use administrative or other IT-centric interfaces fall short of offering an independent and universal approach to data preparation. In addition to supporting conventional data sources and systems Datawatch handles content and documents to help establish a consistent approach to preparing all data needed in business with one tool.
With its heritage in data preparation Datawatch is well positioned to be on the short list of tools that help organizations realize the full value of information assets from inside or outside of the business. We recommend that organizations consider Datawatch and its advances in Monarch 13 for meeting a broader set of data preparation needs.
CEO and Chief Research Officer
Ventana Research defines product information management (PIM) as the practice of using information, applications and other technology to effectively support product-related processes across the customer, commerce and supply chain. As organizations increase the number and diversity of products and services they offer to customers and partners, they increasingly need to address limitations in the ways they manage and distribute product information, including related attributes and content that describes the products. At the same time, competitive pressures require them to be able to incorporate large amounts of new content – video and images, for example – quickly while ensuring that the information presented to customers is accurate, operational processes run uninterrupted and timely data is available for business analysis. In an environment in which consumers, suppliers and partners use multiple channels to get to product information – including websites, kiosks, smartphones and tablets – it is essential that the organization always be able to present complete and up-to-date product information to inspire interest and facilitate purchases.
Product information management and the applications and technology that enable it are designed to help businesses provide the best possible product information to their departments and partners. To accomplish this, PIM software must support multiple business roles, from product managers and marketers to operations and manufacturing teams and to suppliers and those in the supply chain. Manufacturers, for example, need to share product information with distributors and with direct retailers or digital commerce providers on the Internet. For finance and operations departments, effective use of product information increases the efficiency of business processes and reduces the risk of using improper information that could reduce profitability and degrade the customer experience.
Effectively managed information about products is also essential to support a range of decision-making about products and services. Analytics applied to product information can yield a variety of metrics; they can indicate where product information is missing, where it needs to be improved, patterns of product usage and the meaning of feedback about them. In the preparation of product information, analytics can help profile and improve the quality of data and associated attributes to reveal where action must be taken.
Product information management is not the same as master data management (MDM), although the two sometimes are confused. This misunderstanding can distract businesses from focusing on what they need in a PIM application. MDM technology can ensure a single definition of data across the enterprise and improve the quality and integration of data across information systems. Many PIM systems have built-in MDM and now data integration and data quality processes to ensure there is only one defined master record for any given product.
It is important to realize that product information encompasses more than just the defined name and attributes of a product in a database; it includes all related information needed for reference or compliance purposes. Organizations should take care to understand the differences between PIM and MDM as well as how they can complement each other to inform decisions. PIM is essential to enable business units to manage their product-related processes themselves just as IT staff need MDM and integration tools to enable them to manage data throughout the enterprise.
ERP and supply chain applications including product life-cycle management (PLM) have fallen short in meeting the requirements for PIM, leaving many organizations with a lack of consistency in mastering and publishing product information both inside the enterprise and across the supply and demand chain. Commerce software also has lacked depth in providing PIM, a core ingredient for transacting business in products and services. Many commerce providers talk about the importance of focusing on the customer experience, for which effective PIM is a necessity. Web content management software also has a role, but its design is focused on dynamically generating content from a database and personalizing it for business. The lack of maturity in these software categories creates a role for PIM software that can interoperate across business processes and applications.
The goal of PIM is to establish a reliable single source of product information that can be shared across channels. Getting it right is not easy; our benchmark research shows that more than one-quarter of organizations have more than 10 sources of product information that they must integrate and manage efficiently. Half of participants in our research acknowledged that standardizing product information requires substantial effort, and only 27 percent said they completely trust their product information.
In their efforts to produce a reliable product record, most organizations use laborious, time-consuming methods: 37 percent develop custom code, and 45 percent rely on manual effort. One-third of all participants still depend heavily on spreadsheets to create their product records, and almost half (46%) depend on them somewhat. And nearly all (94%) spreadsheet users find major or minor errors in their records.
Processes and tools are available that can automate much of this work. If properly deployed, PIM systems can synchronize all attributes and definitions used in the identification, description, sales and fulfillment of products across all channels that customers, suppliers, trading partners and employees use. Some businesses are implementing PIM that has master data management embedded within it while others connect PIM to their IT organization’s MDM, which can help improve the consistency and quality of data across the enterprise. PIM and MDM projects typically incorporate tools for data discovery, profiling and quality verification to deepen understanding of the data, including relationships and associations among items. This knowledge can be essential for integrating content and data from multiple sources and defining master data.
MDM software by itself and without a PIM context is just for the data infrastructure; this in recent years has slowed its adoption as what is commonly called big data complicates data transformation and creates challenges in adapting to business applications. MDM vendors that continue to insist that their products address PIM often find the decline of interest challenging their market relevance. In contrast, independent vendors focused on PIM have enjoyed a growing market presence in recent years. But just focusing on PIM has its own challenges as organizations look for simpler and more interconnected systems that utilize cloud computing and software as a service; many of these vendors have not moved rapidly enough to support these changes.
The benefits of using dedicated PIM technology can be significant. More than 40 percent of organizations said it can help eliminate data errors, improve cross-sell and up-sell opportunities and improve the customer experience through consistent product information. Yet our research indicates that most organizations have not adopted more capable systems: Only 27 percent use commercial software dedicated to PIM, although more than half (57%) said they will change their PIM system within 12 to 18 months. The latter finding in particular underscores the importance of having a reliable guide such as our 2015 Value Index for PIM which can help companies assess and evaluate vendors and products in this software category. I summarize our analysis in another analyst perspective to illuminate further how it can assist your efforts.
CEO & Chief Research Officer